Yale researchers find key to predicting outcomes of autism treatment

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Yale University researchers report they can predict whether a preschool age child will respond to at least one form of treatment by looking at patterns of the child’s brain activity.

The ability to predict treatment outcomes during a child’s preschool years is crucial, say the researchers, because early intervention with effective treatments can dramatically improve outcomes and can have huge cost savings.

Currently the lifetime cost of supporting those with autism spectrum disorders (ASD) can range from $1.4 million to $2.4 million per child.

I have been working with autistic kids for 20 years and find it impossible to predict who will respond to evidence-based treatments we use. But these neuroimaging biomarkers may help us quickly identify individuals for whom the costly treatments will not work so we can start a more appropriate therapy.

Said Pamela Ventola, assistant professor in the Yale Child Study Center and senior author of the paper published in the journal Translational Psychiatry.

The Yale team analysed functional magnetic resonance imaging (fMRI) data in a sample of 20 (7 girls and 13 boys) young, cognitively able children with ASD before and after they underwent 16 weeks of therapy with an evidence-based program called Pivotal Response Treatment.

PRT, is one of a very few evidence-based treatments for children with ASD. It targets pivotal areas, including social initiation and social responsivity with the premise that improvements in these areas lead to more widespread and generalised improvements in other developmental domains.

By studying patterns of activity in an area of the orbitofrontal cortex involved in social processing, the researchers were able to predict which children would respond to therapy.

The study concludes:

‘Early childhood provides an important window of opportunity for intervention in ASD. The promise of targeted, individualized, precision treatment for core deficits in ASD depends on sensitive, objective biomarkers that can predict how individual young children with ASD will respond to specific treatment(s).

‘For the first time in the field of ASD, we provide evidence that neural signatures in brain circuits implicated in social information processing and social motivation/reward can predict treatment effectiveness at the individual level in young boys and girls with ASD. The results open a new avenue for important future research and should greatly accelerate progress toward more precise and effective treatments for core deficits in ASD.’

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